Triple
T11869066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 63rd Street–Lexington Avenue |
E282359
|
entity |
| Predicate | servedByTrain |
P6301
|
FINISHED |
| Object | Q |
E78745
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Q | Statement: [63rd Street–Lexington Avenue, servedByTrain, Q]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Q Context triple: [63rd Street–Lexington Avenue, servedByTrain, Q]
-
A.
Q
Q is a recurring comedic character from the James Bond film series, known as the eccentric head of MI6's gadget and technology division.
-
B.
Q
Q is a powerful, omnipotent trickster from the Q Continuum who frequently tests and torments the crew of the USS Enterprise in Star Trek: The Next Generation.
-
C.
Q
chosen
The Q is a New York City Subway service that runs along the BMT Broadway Line in Manhattan and the Brighton Line in Brooklyn, providing crosstown and interborough transit.
-
D.
QUE
QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
-
E.
QUE
QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a73c04e4819084c0b2ff8e5d2f04 |
completed | April 10, 2026, 7:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f281a2abfc8190a4769e637dedaaab |
completed | April 29, 2026, 10:09 p.m. |
Created at: April 8, 2026, 9:43 p.m.